store = {}
store['args']={'batch_size': 64, 'scoring_batch_size': 512, 'test_batch_size': 512, 'validation_set_size': 1024, 'early_stopping_patience': 3, 'epochs': 30, 'epoch_samples': 5056, 'num_inference_samples': 20, 'available_sample_k': 40, 'num_iterations': 20, 'no_cuda': False, 'name': 'bald_40_354594', 'seed': 354594, 'log_interval': 20, 'type': 'AcquisitionFunction.bald'}
store['iterations']=[]
store['initial_samples']=[48419, 55275, 28834, 48040, 378, 11086, 52690, 18252, 24901, 21430, 52798, 15306, 28978, 30856, 3599, 1043, 17641, 30525, 7474, 8626]
store['iterations'].append({'num_epochs': 4, 'test_metrics': {'accuracy': 0.6943, 'nll': 2.158078528213501}, 'chosen_samples': [18819, 16870, 41080, 54266, 1788, 26948, 36324, 47536, 25415, 39473, 16084, 53400, 5977, 41052, 27447, 35526, 4510, 17434, 35373, 2278, 48256, 9408, 36775, 950, 25387, 8008, 51337, 26094, 30496, 35036, 50268, 7944, 29570, 57970, 31712, 391, 9347, 44616, 24440, 6066], 'chosen_samples_score': ['1.200175', '1.2004762', '1.2031357', '1.2073328', '1.2054613', '1.2090945', '1.2093263', '1.2070353', '1.2050219', '1.2085223', '1.2117668', '1.2163267', '1.215054', '1.2521051', '1.2249473', '1.3297127', '1.2452575', '1.4388359', '1.2357138', '1.2848978', '1.2683312', '1.2141454', '1.2696133', '1.3344328', '1.2366407', '1.2664611', '1.2371196', '1.2215698', '1.2175978', '1.3385091', '1.2309304', '1.3058324', '1.2150385', '1.2815919', '1.3295443', '1.218466', '1.2254877', '1.2161437', '1.2223355', '1.2665389']})
store['iterations'].append({'num_epochs': 4, 'test_metrics': {'accuracy': 0.7652, 'nll': 1.2610404102325439}, 'chosen_samples': [9000, 10218, 8942, 59378, 30915, 43648, 41999, 19040, 6005, 17089, 7144, 20145, 16909, 39103, 21877, 59158, 16386, 9948, 4188, 1940, 2152, 8702, 28882, 5993, 21550, 20840, 2554, 3370, 25102, 45291, 29591, 40304, 23558, 5365, 4887, 33162, 10465, 13335, 25050, 45157], 'chosen_samples_score': ['0.86293095', '0.86349624', '0.86723894', '0.8647508', '0.8666614', '0.8734367', '0.87341034', '0.86995786', '0.8670115', '0.8676164', '0.87519926', '0.8663767', '0.8748849', '0.8675404', '0.87556607', '0.8945606', '0.94077224', '0.9085625', '0.898119', '0.94872075', '0.889218', '0.9226447', '0.92625695', '0.9046729', '0.88676345', '0.88103515', '0.87731665', '0.89747787', '0.8831449', '0.8851527', '0.8908662', '0.90324515', '0.8821044', '0.9144628', '0.8796205', '0.8817993', '0.9397041', '0.9047941', '0.88838154', '0.8960303']})
store['iterations'].append({'num_epochs': 4, 'test_metrics': {'accuracy': 0.8352, 'nll': 0.8831943731307983}, 'chosen_samples': [47651, 50483, 50381, 11202, 5430, 25453, 34551, 27193, 50006, 32451, 50574, 24621, 49202, 55579, 28512, 10244, 47787, 33593, 51832, 22673, 37489, 6644, 42333, 37137, 47140, 48865, 6650, 3719, 11359, 49322, 28279, 46960, 57342, 13096, 31456, 991, 3694, 47613, 7033, 16992], 'chosen_samples_score': ['0.70703757', '0.7098719', '0.7071936', '0.7102345', '0.71091217', '0.7228384', '0.71462387', '0.74890226', '0.77626944', '0.72909915', '0.7167267', '0.7312904', '0.8228905', '0.7274374', '0.71718615', '0.71219194', '0.7439758', '0.7337524', '0.7119611', '0.7157259', '0.72325313', '0.7492449', '0.73430425', '0.73226106', '0.73635614', '0.7309651', '0.7346005', '0.74244416', '0.738139', '0.7141249', '0.7304358', '0.7520823', '0.73367167', '0.7151068', '0.75824285', '0.73770845', '0.72702795', '0.803795', '0.79007906', '0.71127164']})
store['iterations'].append({'num_epochs': 8, 'test_metrics': {'accuracy': 0.911, 'nll': 0.6330773007392884}, 'chosen_samples': [37118, 42746, 32447, 4476, 28643, 25986, 39841, 14760, 6466, 20363, 32193, 59289, 41505, 30464, 41491, 35128, 34685, 52785, 20448, 58793, 17409, 31284, 20987, 35654, 8458, 20903, 55743, 18426, 41540, 26733, 2078, 36363, 48349, 10473, 44131, 28954, 36403, 56454, 23486, 11619], 'chosen_samples_score': ['0.98740137', '0.99078804', '0.9907226', '0.99193686', '1.0431364', '1.0289471', '1.0130143', '1.0212586', '1.1701488', '0.9928923', '1.1494095', '1.0246084', '0.9955577', '1.0064206', '1.0083907', '1.0976573', '1.0080254', '1.0316777', '1.0216277', '1.0058699', '0.9920521', '1.030707', '1.0012748', '1.0372517', '1.1227889', '1.0225072', '1.0057795', '1.038948', '1.0230218', '1.1387521', '1.0257573', '1.0631119', '1.0551175', '0.99689466', '1.0681468', '0.9976955', '1.0557287', '0.9939125', '1.0137118', '1.1604052']})
store['iterations'].append({'num_epochs': 6, 'test_metrics': {'accuracy': 0.9088, 'nll': 0.5660238739013672}, 'chosen_samples': [16951, 5314, 15801, 42734, 7438, 51306, 22083, 53746, 26398, 45774, 1674, 10736, 6309, 10650, 53873, 55513, 18656, 29938, 33812, 49809, 40846, 5013, 43052, 57714, 37962, 55496, 31301, 7219, 49482, 57820, 39546, 2034, 15730, 10260, 18003, 25910, 11074, 30692, 2000, 8339], 'chosen_samples_score': ['0.8142449', '0.81491625', '0.81550515', '0.8157707', '0.81650984', '0.81659067', '0.8689522', '0.8667976', '0.87348264', '0.8227505', '0.81717116', '0.86614555', '0.81948006', '0.830727', '0.8203784', '0.8553916', '0.848543', '0.82629216', '0.9412053', '0.8733542', '0.82359546', '0.96241784', '0.857332', '0.9394543', '0.8360649', '0.8741631', '1.0198054', '0.8292656', '0.82636315', '0.93416005', '0.89248353', '0.82337976', '0.8496375', '0.8483516', '0.8700604', '0.8211449', '0.89870995', '0.8249587', '0.86074305', '0.87486744']})
store['iterations'].append({'num_epochs': 7, 'test_metrics': {'accuracy': 0.9277, 'nll': 0.4864993025779724}, 'chosen_samples': [37048, 49854, 5790, 22677, 29180, 2036, 14139, 22364, 36818, 14305, 12934, 43224, 57882, 9810, 50320, 53298, 40267, 49227, 48820, 4153, 18904, 42317, 59314, 27514, 27169, 22130, 28491, 2845, 37339, 262, 56662, 40942, 34946, 8892, 1374, 10622, 42428, 45602, 31308, 40066], 'chosen_samples_score': ['0.8786476', '0.87926567', '0.87979215', '0.88013077', '0.88855565', '0.890677', '0.8943198', '0.9004833', '0.9003116', '0.8989534', '0.90172637', '0.969621', '1.01458', '0.94364244', '0.91791886', '0.9841444', '0.95921695', '0.9894235', '0.91984427', '0.9475234', '0.90256244', '0.9523239', '0.98793715', '0.98631287', '0.90724075', '1.013556', '0.91857916', '0.9987076', '0.9473899', '1.1206961', '0.9150832', '0.93570757', '0.9529211', '1.0129445', '0.9294248', '0.9313682', '0.92055875', '0.9702964', '0.94439965', '0.9616339']})
store['iterations'].append({'num_epochs': 8, 'test_metrics': {'accuracy': 0.948, 'nll': 0.40671678047180176}, 'chosen_samples': [7984, 11572, 42020, 17540, 8954, 5315, 59343, 52686, 2611, 2352, 28136, 32702, 41572, 59747, 25823, 17777, 59294, 16286, 59286, 3030, 42828, 16011, 23350, 49624, 11514, 31562, 30418, 16953, 5545, 9804, 36744, 56388, 36732, 11482, 22481, 42703, 53574, 18720, 28102, 22272], 'chosen_samples_score': ['0.89564323', '0.89849055', '0.901624', '0.8974661', '0.90462005', '1.0032073', '1.1354456', '0.9279215', '0.91775656', '0.9281201', '0.9690443', '1.0303841', '0.9208873', '0.9214635', '0.92151576', '1.0209215', '0.9171666', '0.95555294', '0.93142056', '0.9704458', '1.0466349', '0.95424193', '0.9879649', '0.9570547', '1.0393988', '0.91283035', '0.998725', '0.95841634', '0.9512921', '0.9809277', '0.94794023', '0.99755913', '0.927097', '0.93620604', '0.96457165', '0.966881', '0.9315481', '0.9402831', '0.92994255', '0.9637881']})
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store['iterations'].append({'num_epochs': 6, 'test_metrics': {'accuracy': 0.9493, 'nll': 0.39879558458328246}, 'chosen_samples': [46088, 48038, 37469, 27431, 39355, 47741, 4822, 57628, 21880, 49859, 33338, 109, 32276, 48407, 31738, 8833, 12494, 17494, 3056, 57041, 602, 47925, 31184, 9567, 52169, 31954, 12422, 36515, 19089, 23028, 51158, 43048, 44870, 4600, 43532, 13243, 51903, 54896, 32747, 32537], 'chosen_samples_score': ['0.7229387', '0.7229895', '0.7314596', '0.7312716', '0.72767985', '0.727173', '0.72970563', '0.72374403', '0.72343045', '0.72615', '0.73206085', '0.73202956', '0.7325409', '0.7344774', '0.73342717', '0.7374528', '0.73705876', '0.7359953', '0.7409404', '0.7348087', '0.75012', '0.7556408', '0.7572688', '0.7611548', '0.75598305', '0.7592716', '0.7541988', '0.76242095', '0.85588074', '0.76704407', '0.7745266', '0.77225184', '0.82884794', '0.7855603', '0.8199143', '0.78553396', '0.789112', '0.77578163', '0.7998153', '0.8072526']})
store['iterations'].append({'num_epochs': 12, 'test_metrics': {'accuracy': 0.9606, 'nll': 0.35026107869148254}, 'chosen_samples': [31126, 22053, 1075, 38656, 16572, 40334, 34486, 17322, 42787, 14790, 32880, 59283, 31919, 43226, 6289, 22531, 46432, 31289, 47220, 8297, 14589, 8045, 6050, 47209, 43038, 34920, 34942, 27427, 17603, 442, 28362, 43194, 25159, 52140, 7406, 45185, 26358, 28988, 49282, 55244], 'chosen_samples_score': ['0.91166973', '0.9119021', '1.0994153', '1.0682392', '0.95961934', '0.920931', '0.97459894', '1.0364124', '0.9261488', '0.93645', '0.9128379', '0.93750226', '1.0072231', '1.0649822', '0.9622427', '1.0311482', '0.9491046', '0.94790196', '0.9192966', '0.9145773', '0.91973853', '0.9698911', '0.9753567', '0.9250516', '1.134264', '0.9248543', '0.9178785', '0.92575777', '1.0442293', '0.98129493', '1.0931286', '0.9244213', '1.0936375', '1.1799161', '0.9481698', '0.96525675', '1.0112292', '0.9141823', '0.9367629', '1.0776956']})
store['iterations'].append({'num_epochs': 9, 'test_metrics': {'accuracy': 0.9607, 'nll': 0.32920668597221375}, 'chosen_samples': [11292, 32391, 32387, 6365, 48681, 36408, 32776, 52358, 13969, 49683, 31650, 46375, 21150, 47680, 15836, 22838, 21532, 2801, 31345, 29294, 21636, 7146, 14100, 47036, 28633, 18501, 10565, 15510, 57718, 46412, 7833, 48480, 24424, 41464, 27358, 27292, 46391, 49082, 46368, 35401], 'chosen_samples_score': ['0.7808299', '0.7818787', '0.78219306', '0.78217477', '0.78222287', '0.79170996', '0.81705266', '0.81490946', '0.78358614', '0.80869687', '0.80390614', '0.79455745', '0.8198397', '0.818802', '0.8102373', '0.7899075', '0.803639', '0.7873594', '0.81991184', '0.84263784', '0.8267215', '0.83374363', '0.8247392', '0.8244063', '0.8426116', '0.8316876', '0.84484076', '0.8360314', '0.8477805', '0.93507355', '0.8505447', '0.8718384', '0.8735325', '0.8723581', '0.9261132', '0.85975575', '0.89094794', '0.8499592', '0.974131', '0.88184327']})
store['iterations'].append({'num_epochs': 15, 'test_metrics': {'accuracy': 0.9668, 'nll': 0.30960312118530275}, 'chosen_samples': [17855, 29672, 5554, 52873, 32573, 28734, 49890, 48492, 36196, 18348, 28368, 26588, 20150, 2381, 24462, 47479, 20628, 51986, 6893, 19502, 16488, 56468, 13942, 14881, 6832, 43126, 5616, 48102, 488, 53496, 3810, 20230, 49354, 37078, 40184, 41453, 50431, 12651, 48382, 33380], 'chosen_samples_score': ['0.9411082', '0.9415695', '0.94373405', '0.94669026', '0.95781344', '0.98062706', '0.96788144', '0.95026916', '0.9702831', '0.9900769', '0.97491455', '0.9769208', '0.96778876', '0.94395983', '0.95050216', '0.9569845', '0.9785137', '0.9678038', '0.9442402', '0.99042153', '1.0317042', '1.1213204', '1.0905117', '1.0700359', '0.99817455', '0.9999089', '1.0406914', '1.0096555', '0.9929037', '1.0363095', '1.0252787', '0.99618083', '1.079859', '1.0381935', '1.185857', '1.0063654', '1.1056945', '1.0190991', '1.1220851', '1.0038741']})
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